Standard errors in panel regressions can easily be distorted by violations of classical assumptions. Heteroskedasticity
or equivalently:
This article originally appeared as a contributed guide for researchers using Stata for panel data analysis. For updates and advanced topics like spatial panel models or panel VAR, stay tuned for Part 2.
reshape long income_, i(id) j(year)
In a Fixed Effects framework, you can test for groupwise heteroskedasticity using a modified Wald test via the user-written command xttest3 : ssc install xttest3 xtreg income education age, fe xttest3 Use code with caution. Dynamic Panel Data (GMM)
When dealing with complex economic or financial dynamics, basic static models may fall short. Stata offers built-in tools for advanced configurations. Dynamic Panel Data (GMM Estimators)
Once declared, Stata:
xttest0
The workhorse model. Removes all time-invariant unobserved heterogeneity by demeaning each panel's data. Only estimates effects of variables that vary within units over time.
), reject the null hypothesis. This means you should use the model. If the p-value is large ( >0.05is greater than 0.05 stata panel data
For a dataset of companies id observed across years year , the command is:
Data may arrive in "wide" format (one row per unit, columns for each year). Use reshape long to convert to "long" format, which Stata requires.
Crucial for dynamic models: